Introduction

Load libraries

library(Seurat)
library(canceRbits)
library(dplyr)
library(patchwork)
library(DT)
library(SCpubr)
library(tibble)
library(dittoSeq)
library(scRepertoire)
library(reshape2)
library(viridis)
library(tidyr)

library(grDevices)
library(ggpubr)
library(ggplot2)
library(ggnewscale)

library(RColorBrewer)
library(scales)

library(enrichplot)
library(clusterProfiler)
library("org.Hs.eg.db")
library(DOSE)
library(msigdbr)
library(stringr)

path to data

# path to data, to be adapted - serve here to get raw data
path_to_data = file.path("mnt_data","BCC_2023-06/biomedical-sequencing.at/projects/BSA_0460_MF_BCC_1ab413522d3e4d2d959b1b8f2681cf06/COUNT/")


# Load seurat object containing single cell pre-processed and annotated data, in the metadata folder

srat <- readRDS( "20241005_Ressler2024_NeoBCC.Rds")
meta <- srat@meta.data
meta$WHO <- "SD"
meta$WHO[meta$patient %in% c("NeoBCC007_post", "NeoBCC008_post", "NeoBCC012_post", "NeoBCC017_post")] <- "CR"
meta$WHO[meta$patient %in% c("NeoBCC004_post", "NeoBCC006_post", "NeoBCC010_post", "NeoBCC011_post")] <- "PR"
srat <- AddMetaData(srat, meta$WHO, col.name = "WHO")
srat$WHO <- factor(srat$WHO, levels = c("CR", "PR", "SD"))

colors

colors_B <- c(
  "34" = "#ae017e",
  "7"  =  "#377eb8",
  "21" =  "#f781bf",  
  "38" = "#fed976",
  "15" = "#a6cee3" ,
  "22" = "#e31a1c"   ,
   "3" = "#9e9ac8",
 "4"   = "#fdb462" ,
 "24"  = "#b3de69"
)


colors_clonotype = c("Small (1e-04 < X <= 0.001)"   = "#8c6bb1",
           "Medium (0.001 < X <= 0.01)"   = "#41b6c4",
           "Large (0.01 < X <= 0.1)"      = "#fec44f",
           "Hyperexpanded (0.1 < X <= 1)" = "#ce1256"
)

colors_Ig = c("IGHA1" = "#addd8e",
           "IGHA2" = "#238443",
           "IGHM"  = "#dd3497" , 
           "IGHD"  =  "#41b6c4",
           "IGHG1" = "#fec44f",
           "IGHG2" = "#fe9929",
           "IGHG3" = "#ec7014",
           "IGHG4" = "#fee391"
)

Figure 5a

s   <- subset(srat, subset = anno_l1 %in% c("B cells","Plasma cells"))

s@meta.data$seurat_clusters <- factor(s@meta.data$seurat_clusters, levels=c("34","7", "21",  "38",
                                                                             "15", "22","3", "4", "24"))
    
p <- SCpubr::do_DimPlot(sample = s, 
                   reduction = "umap", 
                   label = TRUE, 
                   repel = TRUE, 
                   label.color = "black", 
                   legend.position = "none", 
                   group.by = "seurat_clusters", 
                   font.size = 25,
                   pt.size = 0.5, 
                   colors.use = colors_B) + theme_minimal()  + NoLegend() + theme(text = element_text(size=20))

p

DT::datatable(p$data, 
              caption = ("Figure 5a"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))

Figure 5b

Idents(s) <- s$seurat_clusters

genes <- list( "B" = c("MS4A1", "CD19"),
               "Ag presentation" = c("HLA-DRA", "HLA-DRB1", "HLA-DPB1", "CD40"),
               "Cytotox" = c("GZMK", "PRF1"),
               "Mem" = "CD27",
               "Plasma" = c("IGKC", "IGHG1", "CD38", "SDC1", "JCHAIN"),
               "Cell state" = c("G2M.Score", "S.Score","percent.mito")  
               )

p <- SCpubr::do_DotPlot(sample = s, 
                        features = genes, 
                        font.size = 18, 
                        legend.length = 12,  
                        legend.type = "colorbar", 
                        dot.scale = 8,  
                        colors.use  = c("#7fbc41","#b8e186", "#f7f7f7","#fde0ef", "#c51b7d"), 
                        use_viridis = FALSE
) 

p

DT::datatable(p$data, 
              caption = ("Figure 5b"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))

Figure 5c

q1 <- SCpubr::do_BarPlot( s,
                         group.by = "seurat_clusters",
                         split.by = "WHO",
                         position = "fill",
                         flip = TRUE,
                         order=FALSE,
                         legend.position = "none",
                         font.size = 32 ,
                         colors.use = colors_B,
                         xlab = "",
                         ylab = ""
                          
                   ) + xlab("Response") + ylab("% of B and plasma cells")



q1

DT::datatable(q1$data, 
              caption = ("Figure 5c"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))
q1 <- SCpubr::do_BarPlot( s,
                         group.by = "seurat_clusters",
                         split.by = "Pathological.Response",
                         position = "fill",
                         flip = TRUE,
                         order=FALSE,
                         legend.position = "none",
                         font.size = 32 ,
                         colors.use = colors_B,
                         xlab = "",
                         ylab = ""
                          
                   ) + xlab("Response") + ylab("% of B and plasma cells")



q1

DT::datatable(q1$data, 
              caption = ("Figure 5c"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))

Open and pre-process clonotyoe data

combined <- readRDS("Ressler2024/metadata/100_CombinedBCR.Rds")

srat <- RenameCells(srat,new.names = paste0(srat$patient, "_",gsub("(_1|_2|_3|_4|_5|_6|_7|_8|_9)*", "",colnames(srat))))
srat <- RenameCells(srat,new.names = gsub("_post", "",colnames(srat)))

srat$sample <- gsub("_post", "",srat$patient)


seurat <- combineExpression(combined, srat, 
                  cloneCall = "strict", 
                  group.by = "sample", chain = "both",
                  proportion = TRUE,
                  filterNA = TRUE)



s   <- subset(seurat, subset = anno_l1 %in%  c("B cells","Plasma cells") )

#s@meta.data$anno_l1 <- droplevels(s@meta.data$anno_l1)
#s@meta.data$seurat_clusters <- droplevels(s@meta.data$seurat_clusters)

s@meta.data$cloneType <- factor(s@meta.data$cloneType, levels = unique(s$cloneType))

Figure 5d

done on the highly confident B and plasma cells with exactly 2 IGH and IGL chains

df <- s@meta.data

df <- df %>% 
    separate( CTgene, c("IGH", "IGL"), sep = "_") %>%
  separate( IGH, c("V", "D", "J", "C"), "\\.")
   
 
s <- AddMetaData(s, df$C, col.name = "Ig_level")
sss <- subset(s, subset = Ig_level != "NA")
dim(sss)
## [1] 27974 13045
sss@meta.data$cloneType <- factor(sss@meta.data$cloneType, levels = c("Hyperexpanded (0.1 < X <= 1)", "Large (0.01 < X <= 0.1)", "Medium (0.001 < X <= 0.01)", "Small (1e-04 < X <= 0.001)"))

# define cell group membership
Idents(sss) <- sss$cloneType




sss@meta.data$Ig_level <- factor(sss@meta.data$Ig_level, levels = c("IGHA1",
         "IGHA2",
         "IGHM", 
         "IGHD",
         "IGHG1",
         "IGHG2",
         "IGHG3",
         "IGHG4"))


 

q1 <- SCpubr::do_BarPlot( sss,
                         group.by = "Ig_level",
                         split.by = "anno_l1",
                         position = "fill",
                         flip = TRUE,
                         order=FALSE,
                         legend.position = "right",
                         font.size = 30     , 
                         colors.use = colors_Ig) +
  xlab("") +
  ylab("Frequency of Ig isotypes")



q1

DT::datatable(q1$data, 
              caption = ("Figure 5d"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))
q1 <- SCpubr::do_BarPlot( sss,
                         group.by = "Ig_level",
                         split.by = "cloneType",
                         position = "fill",
                         flip = TRUE,
                         order=FALSE,
                         legend.position = "right",
                         font.size = 30     , 
                         colors.use = colors_Ig               ) +
  xlab("") +
  ylab("Frequency of Ig isotypes")



q1

DT::datatable(q1$data, 
              caption = ("Figure 5d"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))

Figure 5f

Idents(s) <- s$seurat_clusters
s@meta.data$seurat_clusters <- factor(s@meta.data$seurat_clusters, levels=c("34","7", "21",  "38",
                                                                             "15", "22","3", "4", "24"))

s@meta.data$cloneType <- factor(s@meta.data$cloneType, levels = c("Hyperexpanded (0.1 < X <= 1)", "Large (0.01 < X <= 0.1)", "Medium (0.001 < X <= 0.01)", "Small (1e-04 < X <= 0.001)"))

# define cell group membership
Idents(s) <- s$cloneType

de_markers <- DElegate::FindAllMarkers2(s, replicate_column = "patient", method = "edger", min_fc = 0, min_rate = 0.1)

signature_h <- de_markers$feature[de_markers$group1=="Hyperexpanded (0.1 < X <= 1)" ]
background <- rownames(s)
library(msigdbr)
library(clusterProfiler)
# enricher for cnet plot
GO_H_gene_sets = msigdbr(species = "human", category = "H")
msigdbr_t2g = GO_H_gene_sets %>% dplyr::distinct(gs_name, gene_symbol) %>% as.data.frame()

ego_h <- enricher(gene = signature_h, universe = background, TERM2GENE = msigdbr_t2g)

 
b <- barplot(ego_h, title = "Hallmarks´enrichment of hyperexpanded clones")


tmp <- b$data

tmp$ID <- str_trunc(tmp$ID, 100, "right")
tmp$ID <- factor(tmp$ID, levels = tmp$ID[order(tmp$Count)])

p <- ggplot(tmp, aes(Count, ID)) +
    geom_bar(stat = "identity", color="black", fill =  colors_clonotype["Hyperexpanded (0.1 < X <= 1)"]) +
   theme_classic()+ 
    geom_text(
        aes(label = (paste( "padj=", format(p.adjust,scientific = TRUE, digits = 2)))),
        color = "black",
        size = 6,
        hjust=1,
        position = position_dodge(0.5)  ) +
     theme(text = element_text(size=18)) +
  ggtitle("Hyperexpanded clones")


p

DT::datatable(p$data, 
              caption = ("Figure 3I"),
              extensions = 'Buttons', 
              options = list( dom = 'Bfrtip',
              buttons = c( 'csv', 'excel')))